{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from cdo import *   # python version\n",
    "cdo = Cdo()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ERA5_north_daily.nc'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdo.daymean(input='../divergence_of_moisture_flux/ERA5_north_1979-2018.nc',output='ERA5_north_daily.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ERA5_east_daily.nc'"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cdo.daymean(input='../divergence_of_moisture_flux/ERA5_east_1979-2018.nc',output='ERA5_east_daily.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds=xr.open_dataset('./boundary.nc')\n",
    "north=ds['north']\n",
    "east=ds['east']\n",
    "south=ds['south']\n",
    "west=ds['west']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fb1dbdea650>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "north.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds2=xr.open_dataset('ERA5_north_daily.nc')\n",
    "flux_north=ds2['p72.162']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "flux_north_mask=flux_north.where(~np.isnan(north.values),other=np.nan)\n",
    "flux_north_mask[0,:,:].plot()\n",
    "\n",
    "flux_north_total=flux_north_mask.mean(axis=(1,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "flux_south_mask=flux_north.where(~np.isnan(south.values),other=np.nan)\n",
    "flux_south_mask[0,:,:].plot()\n",
    "flux_south_total=flux_south_mask.mean(axis=(1,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds3=xr.open_dataset('ERA5_east_daily.nc')\n",
    "flux_east=ds3['p71.162']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "flux_east_mask=flux_east.where(~np.isnan(east.values),other=np.nan)\n",
    "flux_east_mask[0,:,:].plot()\n",
    "\n",
    "flux_east_total=flux_east_mask.mean(axis=(1,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "flux_west_mask=flux_east.where(~np.isnan(west.values),other=np.nan)\n",
    "flux_west_mask[0,:,:].plot()\n",
    "\n",
    "flux_west_total=flux_west_mask.mean(axis=(1,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 3.59045339e-06  1.52791654e-05  1.06830466e-05 ... -1.32643745e-05\n",
      " -1.25944325e-05 -5.16047294e-06]\n",
      "[-227.59079  -187.11871  -122.22321  ...   43.84917    39.346283\n",
      "   35.378883]\n"
     ]
    }
   ],
   "source": [
    "ds4=xr.open_dataset('fig5.nc')\n",
    "dmf_ano_avg=ds4['dmf_ano_avg'].values\n",
    "heat_ano_avg=ds4['heat_ano_avg'].values\n",
    "print(dmf_ano_avg)\n",
    "print(heat_ano_avg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre>&lt;xarray.DataArray &#x27;p72.162&#x27; (time: 3680, latitude: 61, longitude: 141)&gt;\n",
       "[31651680 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1979-06-01T11:30:00 ... 2018-08-31T11:30:00\n",
       "  * longitude  (longitude) float32 70.0 70.25 70.5 70.75 ... 104.5 104.75 105.0\n",
       "  * latitude   (latitude) float32 40.0 39.75 39.5 39.25 ... 25.5 25.25 25.0\n",
       "Attributes:\n",
       "    long_name:  Vertical integral of northward water vapour flux\n",
       "    units:      kg m**-1 s**-1</pre>"
      ],
      "text/plain": [
       "<xarray.DataArray 'p72.162' (time: 3680, latitude: 61, longitude: 141)>\n",
       "[31651680 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time       (time) datetime64[ns] 1979-06-01T11:30:00 ... 2018-08-31T11:30:00\n",
       "  * longitude  (longitude) float32 70.0 70.25 70.5 70.75 ... 104.5 104.75 105.0\n",
       "  * latitude   (latitude) float32 40.0 39.75 39.5 39.25 ... 25.5 25.25 25.0\n",
       "Attributes:\n",
       "    long_name:  Vertical integral of northward water vapour flux\n",
       "    units:      kg m**-1 s**-1"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "flux_north"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "clm_north=flux_north_total.mean()\n",
    "clm_south=flux_south_total.mean()\n",
    "clm_east=flux_east_total.mean()\n",
    "clm_west=flux_west_total.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "composite_north=flux_north_total[dmf_ano_avg<np.quantile(dmf_ano_avg,0.15)].mean()\n",
    "composite_south=flux_south_total[dmf_ano_avg<np.quantile(dmf_ano_avg,0.15)].mean()\n",
    "composite_east=flux_east_total[dmf_ano_avg<np.quantile(dmf_ano_avg,0.15)].mean()\n",
    "composite_west=flux_west_total[dmf_ano_avg<np.quantile(dmf_ano_avg,0.15)].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<xarray.DataArray 'p72.162' ()>\n",
      "array(1.7144043, dtype=float32), <xarray.DataArray 'p72.162' ()>\n",
      "array(21.08039, dtype=float32), <xarray.DataArray 'p71.162' ()>\n",
      "array(29.8436, dtype=float32), <xarray.DataArray 'p72.162' ()>\n",
      "array(21.08039, dtype=float32)]\n"
     ]
    }
   ],
   "source": [
    "print([clm_north,clm_south,clm_east,clm_south])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[<xarray.DataArray 'p72.162' ()>\n",
      "array(0.05710569, dtype=float32), <xarray.DataArray 'p72.162' ()>\n",
      "array(40.375008, dtype=float32), <xarray.DataArray 'p71.162' ()>\n",
      "array(29.040075, dtype=float32), <xarray.DataArray 'p72.162' ()>\n",
      "array(40.375008, dtype=float32)]\n"
     ]
    }
   ],
   "source": [
    "print([composite_north,composite_south,composite_east,composite_south])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 550.875x370.667 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 370,
       "width": 550
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import proplot as plot\n",
    "f,axs=plot.subplots(axwidth=5,aspect=1.5)\n",
    "\n",
    "ax=axs\n",
    "m1=ax.bar(np.arange(1,5,1),[clm_north,clm_south,clm_east,clm_south],width=0.3,label='Clm')\n",
    "m2=ax.bar(np.arange(1,5,1)+0.4,[composite_north,composite_south,composite_east,composite_south],width=0.3,label='<15%')\n",
    "ax.format(ylim=(0,50),xlim=(0.5,5),ylabel='moisture Flux (Kg/m/s)',\n",
    "         xlocator=1,xticklabels=['north','south','east','west'])\n",
    "ax.legend([m1,m2],ncols=1,loc='ul')\n",
    "f.savefig('fig8.png')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
